DNA Methylation of PI3K/AKT Pathway-Related Genes Predicts Outcome in Patients with Pancreatic Cancer: A Comprehensive Bioinformatics-Based Study

Pancreatic cancer (PCA) is one of the most lethal malignancies worldwide with a 5-year survival rate of 9%. Despite the advances in the field, the need for an earlier detection and effective therapies is paramount. PCA high heterogeneity suggests that epigenetic alterations play a key role in tumour development. However, only few epigenetic biomarkers or therapeutic targets have been identified so far. Here we explored the potential of distinct DNA methylation signatures as biomarkers for early detection and prognosis of PCA. PI3K/AKT-related genes differentially expressed in PCA were identified using the Pancreatic Expression Database (n = 153). Methylation data from PCA patients was obtained from The Cancer Genome Atlas (n = 183), crossed with clinical data to evaluate the biomarker potential of the epigenetic signatures identified and validated in independent cohorts. The majority of selected genes presented higher expression and hypomethylation in tumour tissue. The methylation signatures of specific genes in the PI3K/AKT pathway could distinguish normal from malignant tissue at initial disease stages with AUC > 0.8, revealing their potential as PCA diagnostic tools. ITGA4, SFN, ITGA2, and PIK3R1 methylation levels could be independent prognostic indicators of patients’ survival. Methylation status of SFN and PIK3R1 were also associated with disease recurrence. Our study reveals that the methylation levels of PIK3/AKT genes involved in PCA could be used to diagnose and predict patients’ clinical outcome with high sensitivity and specificity. These results provide new evidence of the potential of epigenetic alterations as biomarkers for disease screening and management and highlight possible therapeutic targets.

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DNA methylome signatures of prenatal exposure to synthetic glucocorticoids in hippocampus and peripheral whole blood of female guinea pigs in early life

Translational Psychiatry ◽

10.1038/s41398-020-01186-6 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Aya Sasaki ◽

Margaret E. Eng ◽

Abigail H. Lee ◽

Alisa Kostaki ◽

Stephen G. Matthews

Keyword(s):

Dna Methylation ◽

Whole Blood ◽

Guinea Pigs ◽

Critical Role ◽

Methylation Status ◽

Peripheral Tissues ◽

Epigenetic Biomarkers ◽

Differentially Methylated Genes ◽

Increased Risk ◽

Synthetic Glucocorticoids

AbstractSynthetic glucocorticoids (sGC) are administered to women at risk of preterm delivery, approximately 10% of all pregnancies. In animal models, offspring exposed to elevated glucocorticoids, either by administration of sGC or endogenous glucocorticoids as a result of maternal stress, show increased risk of developing behavioral, endocrine, and metabolic dysregulation. DNA methylation may play a critical role in long-lasting programming of gene regulation underlying these phenotypes. However, peripheral tissues such as blood are often the only accessible source of DNA for epigenetic analyses in humans. Here, we examined the hypothesis that prenatal sGC administration alters DNA methylation signatures in guinea pig offspring hippocampus and whole blood. We compared these signatures across the two tissue types to assess epigenetic biomarkers of common molecular pathways affected by sGC exposure. Guinea pigs were treated with sGC or saline in late gestation. Genome-wide modifications of DNA methylation were analyzed at single nucleotide resolution using reduced representation bisulfite sequencing in juvenile female offspring. Results indicate that there are tissue-specific as well as common methylation signatures of prenatal sGC exposure. Over 90% of the common methylation signatures associated with sGC exposure showed the same directionality of change in methylation. Among differentially methylated genes, 134 were modified in both hippocampus and blood, of which 61 showed methylation changes at identical CpG sites. Gene pathway analyses indicated that prenatal sGC exposure alters the methylation status of gene clusters involved in brain development. These data indicate concordance across tissues of epigenetic programming in response to alterations in glucocorticoid signaling.

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DNA Methylation Based Molecular Subtypes Predict Prognosis in Breast Cancer Patients

Cancer Control ◽

10.1177/1073274820988519 ◽

2021 ◽

Vol 28 ◽

pp. 107327482098851

Author(s):

Zeng-Hong Wu ◽

Yun Tang ◽

Yan Zhou

Keyword(s):

Breast Cancer ◽

Dna Methylation ◽

Molecular Subtypes ◽

Methylation Status ◽

The Cancer Genome Atlas ◽

Training Dataset ◽

Consensus Clustering ◽

Breast Cancer Patients ◽

Cancer Subtypes ◽

Novel Biomarkers

Background: Epigenetic changes are tightly linked to tumorigenesis development and malignant transformation’ However, DNA methylation occurs earlier and is constant during tumorigenesis. It plays an important role in controlling gene expression in cancer cells. Methods: In this study, we determining the prognostic value of molecular subtypes based on DNA methylation status in breast cancer samples obtained from The Cancer Genome Atlas database (TCGA). Results: Seven clusters and 204 corresponding promoter genes were identified based on consensus clustering using 166 CpG sites that significantly influenced survival outcomes. The overall survival (OS) analysis showed a significant prognostic difference among the 7 groups (p<0.05). Finally, a prognostic model was used to estimate the results of patients on the testing set based on the classification findings of a training dataset DNA methylation subgroups. Conclusions: The model was found to be important in the identification of novel biomarkers and could be of help to patients with different breast cancer subtypes when predicting prognosis, clinical diagnosis and management.

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Epigenetic Alterations in Oesophageal Cancer: Expression and Role of the Involved Enzymes

International Journal of Molecular Sciences ◽

10.3390/ijms21103522 ◽

2020 ◽

Vol 21 (10) ◽

pp. 3522

Author(s):

Nair Lopes ◽

Margareta P. Correia ◽

Rui Henrique ◽

Carmen Jerónimo

Keyword(s):

Oesophageal Cancer ◽

Therapeutic Targets ◽

Normal Mucosa ◽

The Cancer Genome Atlas ◽

Epigenetic Alterations ◽

Life Threatening ◽

Cancer Genome Atlas ◽

In Vitro Data

Oesophageal cancer is a life-threatening disease, accounting for high mortality rates. The poor prognosis of this malignancy is mostly due to late diagnosis and lack of effective therapies for advanced disease. Epigenetic alterations may constitute novel and attractive therapeutic targets, owing to their ubiquity in cancer and their reversible nature. Herein, we offer an overview of the most important studies which compared differences in expression of enzymes that mediate epigenetic alterations between oesophageal cancer and normal mucosa, as well as in vitro data addressing the role of these genes/proteins in oesophageal cancer. Furthermore, The Cancer Genome Atlas database was interrogated for the correlation between expression of these epigenetic markers and standard clinicopathological features. We concluded that most epigenetic players studied thus far are overexpressed in tumours compared to normal tissue. Furthermore, functional assays suggest an oncogenic role for most of those enzymes, supporting their potential as therapeutic targets in oesophageal cancer.

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Identification of prostate cancer specific methylation biomarkers from a multi-cancer analysis

BMC Bioinformatics ◽

10.1186/s12859-021-04416-w ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Yiyi Pu ◽

Chao Li ◽

Haining Yuan ◽

Xiaoju Wang

Keyword(s):

Prostate Cancer ◽

Dna Methylation ◽

In Silico ◽

Prostate Cancer Screening ◽

Methylation Status ◽

The Cancer Genome Atlas ◽

Translation Rate ◽

Normal Prostate ◽

Cancer Data ◽

Significant Difference

Abstract Background Detecting prostate cancer at a non-aggressive stage is the main goal of prostate cancer screening. DNA methylation has been widely used as biomarkers for cancer diagnosis and prognosis, however, with low clinical translation rate. By taking advantage of multi-cancer data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), we aimed to identify prostate cancer specific biomarkers which can separate between non-aggressive and aggressive prostate cancer based on DNA methylation patterns. Results We performed a comparison analysis of DNA methylation status between normal prostate tissues and prostate adenocarcinoma (PRAD) samples at different Gleason stages. The candidate biomarkers were selected by excluding the biomarkers existing in multiple cancers (pan-cancer) and requiring significant difference between PRAD and other urinary samples. By least absolute shrinkage and selection operator (LASSO) selection, 8 biomarkers (cg04633600, cg05219445, cg05796128, cg10834205, cg16736826, cg23523811, cg23881697, cg24755931) were identified and in-silico validated by model constructions. First, all 8 biomarkers could separate PRAD at different stages (Gleason 6 vs. Gleason 3 + 4: AUC = 0.63; Gleason 6 vs. Gleason 4 + 3 and 8–10: AUC = 0.87). Second, 5 biomarkers (cg04633600, cg05796128, cg23523811, cg23881697, cg24755931) effectively detected PRAD from normal prostate tissues (AUC ranged from 0.88 to 0.92). Last, 6 biomarkers (cg04633600, cg05219445, cg05796128, cg23523811, cg23881697, cg24755931) completely distinguished PRAD with other urinary samples (AUC = 1). Conclusions Our study identified and in-silico validated a panel of prostate cancer specific DNA methylation biomarkers with diagnosis value.

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An analytical pipeline for DNA Methylation Array Biomarker Studies

10.1101/2021.07.14.452293 ◽

2021 ◽

Author(s):

Jennifer Lu ◽

Darren Korbie ◽

Matt Trau

Keyword(s):

Dna Methylation ◽

Feature Selection ◽

Differential Methylation ◽

The Cancer Genome Atlas ◽

Methylation Array ◽

Epigenetic Biomarkers ◽

Cancer Genome Atlas ◽

Dna Methylation Array ◽

Methylation Patterns ◽

Selection Of

DNA methylation is one of the most commonly studied epigenetic biomarkers, due to its role in disease and development. The Illumina Infinium methylation arrays still remains the most common method to interrogate methylation across the human genome, due to its capabilities of screening over 480, 000 loci simultaneously. As such, initiatives such as The Cancer Genome Atlas (TCGA) have utilized this technology to examine the methylation profile of over 20,000 cancer samples. There is a growing body of methods for pre-processing, normalisation and analysis of array-based DNA methylation data. However, the shape and sampling distribution of probe-wise methylation that could influence the way data should be examined was rarely discussed. Therefore, this article introduces a pipeline that predicts the shape and distribution of normalised methylation patterns prior to selection of the most optimal inferential statistics screen for differential methylation. Additionally, we put forward an alternative pipeline, which employed feature selection, and demonstrate its ability to select for biomarkers with outstanding differences in methylation, which does not require the predetermination of the shape or distribution of the data of interest. Availability: The Distribution test and the feature selection pipelines are available for download at: https://github.com/uqjlu8/DistributionTest Keywords: DNA methylation, Biomarkers, Cancers, Data Distribution, TCGA, 450K

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Analysis of DNA Methylation Patterns Associated with In Vitro Propagated Globe Artichoke Plants Using an EpiRADseq-Based Approach

Genes ◽

10.3390/genes10040263 ◽

2019 ◽

Vol 10 (4) ◽

pp. 263 ◽

Cited By ~ 2

Author(s):

Elisa Cerruti ◽

Cinzia Comino ◽

Alberto Acquadro ◽

Gianpiero Marconi ◽

Anna Maria Repetto ◽

...

Keyword(s):

Dna Methylation ◽

Methylation Status ◽

Transcriptional Analysis ◽

Globe Artichoke ◽

Epigenetic Alterations ◽

Coding Regions ◽

Methylation Patterns ◽

Reproductive Processes ◽

Photosynthesis Regulation

Globe artichoke represents one of the main horticultural species of the Mediterranean basin, and ‘Spinoso sardo’ is the most widespread and economically relevant varietal type in Sardinia, Italy. In the last decades, in vitro culture of meristematic apices has increased the frequency of aberrant plants in open-field production. These off-type phenotypes showed highly pinnate-parted leaves and late inflorescence budding, and emerged from some branches of the true-to-type ‘Spinoso sardo’ plants. This phenomenon cannot be foreseen and is reversible through generations, suggesting the occurrence of epigenetic alterations. Here, we report an exploratory study on DNA methylation patterns in off-type/true-to-type globe artichoke plants, using a modified EpiRADseq technology, which allowed the identification of 2,897 differentially methylated loci (DML): 1,998 in CG, 458 in CHH, and 441 in CHG methylation contexts of which 720, 88, and 152, respectively, were in coding regions. Most of them appeared involved in primary metabolic processes, mostly linked to photosynthesis, regulation of flower development, and regulation of reproductive processes, coherently with the observed phenotype. Differences in the methylation status of some candidate genes were integrated with transcriptional analysis to test whether these two regulation levels might interplay in the emergence and spread of the ‘Spinoso sardo’ non-conventional phenotype.

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Epigenetic Biomarkers of Renal Cell Carcinoma for Liquid Biopsy Tests

International Journal of Molecular Sciences ◽

10.3390/ijms22168846 ◽

2021 ◽

Vol 22 (16) ◽

pp. 8846

Author(s):

Raimonda Kubiliute ◽

Sonata Jarmalaite

Keyword(s):

Dna Methylation ◽

Liquid Biopsy ◽

Renal Cell ◽

Morphological Changes ◽

Diagnostic Tools ◽

Liquid Biopsies ◽

Non Invasive ◽

Epigenetic Biomarkers ◽

Treatment Changes

Renal cell carcinomas (RCC) account for 2–3% of the global cancer burden and are characterized by the highest mortality rate among all genitourinary cancers. However, excluding conventional imagining approaches, there are no reliable diagnostic and prognostic tools available for clinical use at present. Liquid biopsies, such as urine, serum, and plasma, contain a significant amount of tumor-derived nucleic acids, which may serve as non-invasive biomarkers that are particularly useful for early cancer detection, follow-up, and personalization of treatment. Changes in epigenetic phenomena, such as DNA methylation level, expression of microRNAs (miRNAs), and long noncoding RNAs (lncRNAs), are observed early during cancer development and are easily detectable in biofluids when morphological changes are still undetermined by conventional diagnostic tools. Here, we reviewed recent advances made in the development of liquid biopsy-derived DNA methylation-, miRNAs- and lncRNAs-based biomarkers for RCC, with an emphasis on the performance characteristics. In the last two decades, a mass of circulating epigenetic biomarkers of RCC were suggested, however, most of the studies done thus far analyzed biomarkers selected from the literature, used relatively miniature, local, and heterogeneous cohorts, and suffered from a lack of sufficient validations. In summary, for improved translation into the clinical setting, there is considerable demand for the validation of the existing pool of RCC biomarkers and the discovery of novel ones with better performance and clinical utility.

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Genetic and Epigenetic Alterations Induced by Pesticide Exposure: Integrated Analysis of Gene Expression, microRNA Expression and DNA Methylation Datasets

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18168697 ◽

2021 ◽

Vol 18 (16) ◽

pp. 8697

Author(s):

Federica Giambò ◽

Gian Leone ◽

Giuseppe Gattuso ◽

Roberta Rizzo ◽

Alessia Cosentino ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Pesticide Exposure ◽

Methylation Status ◽

Microrna Expression ◽

Integrated Analysis ◽

Epigenetic Alterations ◽

Expression Levels ◽

Prediction Tools

Environmental or occupational exposure to pesticides is considered one of the main risk factors for the development of various diseases. Behind the development of pesticide-associated pathologies, there are both genetic and epigenetic alterations, where these latter are mainly represented by the alteration in the expression levels of microRNAs and by the change in the methylation status of the DNA. At present, no studies have comprehensively evaluated the genetic and epigenetic alterations induced by pesticides; therefore, the aim of the present study was to identify modifications in gene miRNA expression and DNA methylation useful for the prediction of pesticide exposure. For this purpose, an integrated analysis of gene expression, microRNA expression, and DNA methylation datasets obtained from the GEO DataSets database was performed to identify putative genes, microRNAs, and DNA methylation hotspots associated with pesticide exposure and responsible for the development of different diseases. In addition, DIANA-miRPath, STRING, and GO Panther prediction tools were used to establish the functional role of the putative biomarkers identified. The results obtained demonstrated that pesticides can modulate the expression levels of different genes and induce different epigenetic alterations in the expression levels of miRNAs and in the modulation of DNA methylation status.

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Integrated Analysis of Microarray and RNA-Seq Data for the Identification of Hub Genes and Networks Involved in the Pancreatic Cancer

Frontiers in Genetics ◽

10.3389/fgene.2021.663787 ◽

2021 ◽

Vol 12 ◽

Author(s):

Maryum Nisar ◽

Rehan Zafar Paracha ◽

Iqra Arshad ◽

Sidra Adil ◽

Sabaoon Zeb ◽

...

Keyword(s):

Gene Expression ◽

Pancreatic Cancer ◽

Early Stage ◽

Therapeutic Targets ◽

Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Receptor Interaction ◽

Integrated Analysis ◽

Rna Seq ◽

Hub Genes

Pancreatic cancer (PaCa) is the seventh most fatal malignancy, with more than 90% mortality rate within the first year of diagnosis. Its treatment can be improved the identification of specific therapeutic targets and their relevant pathways. Therefore, the objective of this study is to identify cancer specific biomarkers, therapeutic targets, and their associated pathways involved in the PaCa progression. RNA-seq and microarray datasets were obtained from public repositories such as the European Bioinformatics Institute (EBI) and Gene Expression Omnibus (GEO) databases. Differential gene expression (DE) analysis of data was performed to identify significant differentially expressed genes (DEGs) in PaCa cells in comparison to the normal cells. Gene co-expression network analysis was performed to identify the modules co-expressed genes, which are strongly associated with PaCa and as well as the identification of hub genes in the modules. The key underlaying pathways were obtained from the enrichment analysis of hub genes and studied in the context of PaCa progression. The significant pathways, hub genes, and their expression profile were validated against The Cancer Genome Atlas (TCGA) data, and key biomarkers and therapeutic targets with hub genes were determined. Important hub genes identified included ITGA1, ITGA2, ITGB1, ITGB3, MET, LAMB1, VEGFA, PTK2, and TGFβ1. Enrichment analysis characterizes the involvement of hub genes in multiple pathways. Important ones that are determined are ECM–receptor interaction and focal adhesion pathways. The interaction of overexpressed surface proteins of these pathways with extracellular molecules initiates multiple signaling cascades including stress fiber and lamellipodia formation, PI3K-Akt, MAPK, JAK/STAT, and Wnt signaling pathways. Identified biomarkers may have a strong influence on the PaCa early stage development and progression. Further, analysis of these pathways and hub genes can help in the identification of putative therapeutic targets and development of effective therapies for PaCa.

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Epigenetic Biomarkers as Diagnostic Tools for Neurodegenerative Disorders

International Journal of Molecular Sciences ◽

10.3390/ijms23010013 ◽

2021 ◽

Vol 23 (1) ◽

pp. 13

Author(s):

Olaia Martínez-Iglesias ◽

Vinogran Naidoo ◽

Natalia Cacabelos ◽

Ramón Cacabelos

Keyword(s):

Dna Methylation ◽

Neurodegenerative Diseases ◽

Neurodegenerative Disorders ◽

Buffy Coat ◽

Diagnostic Tools ◽

Bdnf Expression ◽

Diagnostic Efficacy ◽

Neuregulin 1 ◽

Epigenetic Biomarkers ◽

Expression And Activity

Epigenetics is the study of heritable changes in gene expression that occur without alterations to the DNA sequence, linking the genome to its surroundings. The accumulation of epigenetic alterations over the lifespan may contribute to neurodegeneration. The aim of the present study was to identify epigenetic biomarkers for improving diagnostic efficacy in patients with neurodegenerative diseases. We analyzed global DNA methylation, chromatin remodeling/histone modifications, sirtuin (SIRT) expression and activity, and the expression of several important neurodegeneration-related genes. DNA methylation, SIRT expression and activity and neuregulin 1 (NRG1), microtubule-associated protein tau (MAPT) and brain-derived neurotrophic factor (BDNF) expression were reduced in buffy coat samples from patients with neurodegenerative disorders. Our data suggest that these epigenetic biomarkers may be useful in clinical practical for the diagnosis, surveillance, and prognosis of disease activity in patients with neurodegenerative diseases.

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